It is desirable for autonomous vehicles to be able to navigate in an unknown environment. One approach to navigating in an unknown environment is Simultaneous Localization And Map building (SLAM). Map Building refers to locating and estimating the position of landmarks in the unknown environment and Localization refers to estimating the position of the autonomous vehicle relative to the located landmarks. In other words, SLAM constitutes generating a map of the unknown environment and then navigating relative to the generated map.
The autonomous vehicle typically generates the map by using image sensors located on the autonomous vehicle to locate the landmarks. Landmarks can be any fixed object in the area such as trees, parked cars, buildings, statues, etc. The estimated location of the landmarks is initially resolved in the reference frame of the autonomous vehicle (also referred to herein as a vehicle frame) because the image sensors are mounted on the autonomous vehicle. However, in order to navigate effectively, the location of the landmarks must be resolved in a global reference frame (also referred to herein as a navigation frame). In estimating the orientation of the autonomous vehicle in the global frame, heading angle drift, or bias, error is introduced into the calculations.
The heading angle drift error refers to the difference between the actual heading angle and the estimated heading angle. The heading angle bias error introduces errors in the estimated position and velocity of the vehicle in the global frame as compared to the actual position and velocity of the vehicle and the estimated position of the landmarks in the global frame as compared to the actual position of the landmarks in the global frame.
One conventional technique for correcting the heading angle drift error is to compare the estimated location of a known landmark with the actual location of the known landmark. The difference in location is due, in part, to heading angle drift error. However, this technique requires knowledge of the actual location of the landmark. In environments where the actual location of a landmark is not known, the conventional technique can not be used.